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Purpose The Obesity and Disease Development Sweden (ODDS) study was designed to create a large cohort to study body mass index (BMI), waist circumference (WC) and changes in weight and WC, in relation to morbidity and mortality.Participants ODDS includes 4 295 859 individuals, 2 165 048 men and 2 130 811 women, in Swedish cohorts and national registers with information on weight assessed once (2 555 098 individuals) or more (1 740 761 individuals), in total constituting 7 733 901 weight assessments at the age of 17–103 years in 1963–2020 (recalled weight as of 1911). Information on WC is available in 152 089 men and 212 658 women, out of whom 108 795 have repeated information on WC (in total 512 273 assessments). Information on morbidity and mortality was retrieved from national registers, with follow-up until the end of 2019–2021, varying between the registers.Findings to date Among all weight assessments (of which 85% are objectively measured), the median year, age and BMI (IQR) is 1985 (1977–1994) in men and 2001 (1991–2010) in women, age 19 (18–40) years in men and 30 (26–36) years in women and BMI 22.9 (20.9–25.4) kg/m2 in men and 23.2 (21.2–26.1) kg/m2 in women. Normal weight (BMI 18.5–24.9 kg/m2) is present in 67% of assessments in men and 64% in women and obesity (BMI≥30 kg/m2) in 5% of assessments in men and 10% in women. The median (IQR) follow-up time from the first objectively measured or self-reported current weight assessment until emigration, death or end of follow-up is 31.4 (21.8–40.8) years in men and 19.6 (9.3–29.0) years in women. During follow-up, 283 244 men and 123 457 women died.Future plans The large sample size and long follow-up of the ODDS Study will provide robust results on anthropometric measures in relation to risk of common diseases and causes of deaths, and novel findings in subgroups and rarer outcomes.

Abstract Background Ideal cardiovascular health (CVH) can be assessed by 7 metrics: smoking, body mass index, physical activity, diet, hypertension, dyslipidemia and diabetes, proposed by the American Heart Association. We examined the association of ideal CVH metrics with risk of all-cause, CVD and non-CVD death in a large cohort. Methods A total of 29,557 participants in the Swedish National March Cohort were included in this study. We ascertained 3,799 deaths during a median follow-up of 19 years. Cox regression models were used to estimate hazard ratios with 95% confidence intervals (95% CIs) of the association between CVH metrics with risk of death. Laplace regression was used to estimate 25th, 50th and 75th percentiles of age at death. Results Compared with those having 6–7 ideal CVH metrics, participants with 0–2 ideal metrics had 107% (95% CI = 46-192%) excess risk of all-cause, 224% (95% CI = 72-509%) excess risk of CVD and 108% (31-231%) excess risk of non-CVD death. The median age at death among those with 6–7 vs. 0–2 ideal metrics was extended by 4.2 years for all-causes, 5.8 years for CVD and 2.9 years for non-CVD, respectively. The observed associations were stronger among females than males. Conclusions The strong inverse association between number of ideal CVH metrics and risk of death supports the application of the proposed seven metrics for individual risk assessment and general health promotion.

Summary: Background: Obesity, assessed by body mass index (BMI), is an established risk factor for 13 cancers. We aimed to identify further potential obesity-related cancers and to quantify their association with BMI relative to that of established obesity-related cancers. Methods: Using Cox regression models on 4,142,349 individuals in Sweden (mean age 27.1 years at weight measurement), we calculated hazard ratios (HRs) for the association between BMI and the risk of 122 cancers and cancer subtypes, grouped by topography and morphology. Cancers with a positive association (i.e., HR >1) at an α-level of 0.05 for obesity (BMI ≥30 kg/m2) vs. normal weight (BMI 18.5–24.9 kg/m2) or per 5 kg/m2 higher BMI, for which obesity is not an established risk factor, were considered potentially obesity related. Findings: After 100.2 million person-years of follow-up, 332,501 incident cancer cases were recorded. We identified 15 cancers in men and 16 in women as potentially obesity related. These were cancers of the head and neck, gastrointestinal tract, malignant melanoma, genital organs, endocrine organs, connective tissue, and haematological malignancies. Among these, there was evidence of differential associations with BMI between subtypes of gastric cancer, small intestine cancer, cervical cancer, and lymphoid neoplasms (P values for heterogeneity in HRs

Current evidence suggests that dietary vitamin E (as α-tocopherol) intake has a beneficial role in preventing certain chronic diseases. In contrast, there is no clear evidence for the benefit of α-tocopherol supplements in a generally healthy population. Deficiency symptoms are rare and mainly occur due to genetic or other factors affecting α-tocopherol absorption and/or metabolism, rather than a low α-tocopherol intake. No qualified systematic review was identified by the NNR2023 project for updating the dietary reference values (DRV).

Abstract Background Loss of appetite is a common nutrition symptom in patients with cancer. Understanding the trajectory of appetite could be of clinical use for prognostication in palliative cancer care. Our primary aim was to explore the association between self-assessed appetite and mortality in patients suffering from advanced cancer. Secondary aims included the relation between fatigue, albumin levels and CRP/albumin ratio and mortality. We also aimed to study potential sex-differences in the associations. Methods Post-hoc analyses were performed using data from the Palliative D-study comprising 530 patients with cancer admitted to palliative care. Appetite and fatigue were assessed with the Edmonton Symptom Assessment System (ESAS). Cox proportional hazards models were used to calculate Hazard ratios (HR) with 95% confidence intervals (CI) for exposures of appetite, fatigue, albumin and CRP/albumin ratio, and time from study inclusion to death or censoring. Analyses were also performed stratified by sex. Results The follow-up time ranged between 7 to 1420 days. Moderate and poor appetite were significantly associated with a higher mortality rate compared to reporting a good appetite; HR 1.44 (95%CI: 1.16–1.79) and HR 1.78 (95%CI: 1.39–2.29), respectively. A higher mortality rate was also seen among participants reporting severe fatigue compared to those reporting no fatigue; HR 1.84 (95%CI:1.43–2.36). Participants with low albumin levels ( 36 g/L) and those in lowest tertile of CRP/albumin ratio. These associations were more pronounced in men than in women. Conclusion Poor appetite, severe fatigue, low albumin level and a high CRP/albumin ratio were associated with increased mortality rates among patients with advanced cancer. All these variables might be clinically useful for prognostication in palliative cancer care. Trial registration Clinicaltrial.gov. Identifier: NCT03038516;31, January 2017.

Abstract Background Dietary change towards a diet low in greenhouse gas emissions (GHGEs) can reduce climate impact and improve individual-level health. However, there is a lack of understanding if diet interventions can achieve low-GHGE diets. Methods A randomized controlled trial was conducted to assess the effects of an app-based intervention. The intervention was designed to improve dietary intake of people with Type 2 diabetes, and was delivered via an app over 12 weeks, with each week covering one diet-related topic. Dietary intake was assessed at baseline and 3-month follow up by a 95-item food frequency questionnaire and linked to GHGE values. A total of n = 93 participants (n = 46 and n = 47 for the intervention and control group, respectively) were included in the analysis. Changes to GHGEs within and between the groups were analysed with inferential statistics. Results The majority (60%) of participants were male, with a mean age of 63.2 years and body mass index of 30 kg/m2. At baseline, diet-related GHGEs were 4.8 and 4.9 kg CO2-eq/day in the intervention and control group, respectively. At 3-month follow up the corresponding GHGEs were 4.7 and 4.9 kg CO2-eq/day. We found no statistically significant changes to diet-related GHGEs within or between groups, or within food categories, from baseline to 3-month follow up. Conclusion No evidence was found for the effectiveness of the app-based intervention to generate changes to diet-related GHGEs in a population of people with Type 2 diabetes. However, future interventions that target reducing meat consumption specifically may have the potential to result in a reduction of individual-level diet-related GHGEs. Trial registration ClinicalTrials.gov, NCT03784612. Registered 24 December 2018. www.clinicaltrials.gov/ct2/show/NCT03784612 .

BackgroundPhysical activity is well known to have beneficial effects on glycemic control and to reduce risk factors for cardiovascular disease in persons with type 2 diabetes. Yet, successful implementation of lifestyle interventions targeting physical activity in primary care has shown to be difficult. Smartphone apps may provide useful tools to support physical activity. The DiaCert app was specifically designed for integration into primary care and is an automated mobile health (mHealth) solution promoting daily walking. ObjectiveThis study aimed to investigate the effect of a 3-month-long intervention promoting physical activity through the use of the DiaCert app among persons with type 2 diabetes in Sweden. Our primary objective was to assess the effect on moderate to vigorous physical activity (MVPA) at 3 months of follow-up. Our secondary objective was to assess the effect on MVPA at 6 months of follow-up and on BMI, waist circumference, hemoglobin A1c, blood lipids, and blood pressure at 3 and 6 months of follow-up. MethodsWe recruited men and women with type 2 diabetes from 5 primary health care centers and 1 specialized center. Participants were randomized 1:1 to the intervention or control group. The intervention group was administered standard care and access to the DiaCert app at baseline and 3 months onward. The control group received standard care only. Outcomes of objectively measured physical activity using accelerometers, BMI, waist circumference, biomarkers, and blood pressure were assessed at baseline and follow-ups. Linear mixed models were used to assess differences in outcomes between the groups. ResultsA total of 181 study participants, 65.7% (119/181) men and 34.3% (62/181) women, were recruited into the study and randomized to the intervention (n=93) or control group (n=88). The participants’ mean age and BMI were 60.0 (SD 11.4) years and 30.4 (SD 5.3) kg/m2, respectively. We found no significant effect of the intervention (group by time interaction) on MVPA at either the 3-month (β=1.51, 95% CI –5.53 to 8.55) or the 6-month (β=–3.53, 95% CI –10.97 to 3.92) follow-up. We found no effect on any of the secondary outcomes at follow-ups, except for a significant effect on BMI at 6 months (β=0.52, 95% CI 0.20 to 0.84). However, mean BMI did not differ between the groups at the 6-month follow-up. ConclusionsWe found no evidence that persons with type 2 diabetes being randomized to use an app promoting daily walking increased their levels of MVPA at 3 or 6 months’ follow-up compared with controls receiving standard care. The effect of the app on BMI was unclear, and we found nothing to support an effect on secondary outcomes. Further research is needed to determine what type of mHealth intervention could be effective to increase physical activity among persons with type 2 diabetes. Trial RegistrationClinicalTrials.gov NCT03053336; https://clinicaltrials.gov/study/NCT03053336

Abstract Background and Aims Accelerometers collect data in an objective way, however, a number of decisions must be done during data collection, processing and output‐interpretation. The influence of those decisions is seldom investigated, reported, or discussed. Herein, we examined the influence of different decisions on the outcomes: daily minutes of moderate‐to‐vigorous physical activity (MVPA), inactivity and light physical activity (LPA). Methods In total, 156 participants wore an accelerometer (ActiGraph wGT3X‐BT) on their nondominant wrist for 7 days. Data collection was conducted from February 2017 to June 2018. Data was processed using the R‐package GGIR and default settings were compared to by‐the‐literature‐suggested options. The output was examined using paired t‐tests. Results When comparing two commonly used MVPA‐cut‐points, default and Hildebrand et al. we found a marginal difference (0.4 min, 1.0%, p

Introduction: With the rapid development of treatment modalities for obesity management, there is a growing need for guidelines. This was acknowledged by the Swedish National Board of Health and Welfare and in 2020 the process of producing the first national guidelines for obesity care, including both children and adults, was initiated. The main aim was to ensure equal high standard care throughout Sweden by supporting decision makers to allocate resources to the best knowledge-based care. Methods: The standardized procedures of the National Board of Health and Welfare were applied to construct guidelines in a systematic and transparent way, including priority setting of recommendations and quality indicators to evaluate the progress of implementation. The process involved independent expert committees including professionals and patient representatives, and the guidelines were reviewed through an open public consultation. Results: In total, 20 recommendations were issued encompassing a broad scope, from identification and diagnosis to multiple treatment modalities, embedded in a life course perspective from pregnancy to the elderly, as well as highlighting the need for improved knowledge and competence of health care providers. Conclusions: National guidelines for improved standard care and evidence based and efficient use of health care resources for obesity treatment can be developed in a systematic way with professionals and patient representatives.

Abstract Effects of repeated weight changes on mortality are not well established. In this prospective cohort study, we followed 34,346 individuals from 1997 to 2018 for all-cause mortality, and 2016 for cause-specific mortality. At baseline, participants self-reported amount and frequency of prior weight loss. During 20.6 (median) years of follow-up, we identified 5627 deaths; 1783 due to cancer and 1596 due to cardiovascular disease (CVD). We used Cox Proportional Hazards models to estimate multivariable‐adjusted Hazard Ratios (HRs) and 95% confidence intervals (CI). Participants with a weight loss > 10 kg had higher rates of all-cause (HR 1.22; 95%CI 1.09–1.36) and CVD mortality (HR 1.27; 95%CI 1.01–1.59) compared to individuals with no weight loss. Men who had lost > 10 kg had higher all-cause (HR 1.55; 95%CI 1.31–1.84) and CVD mortality (HR 1.55; 95%CI 1.11–2.15) compared to men with no weight loss. Participants who had lost ≥ 5 kg three times or more prior to baseline had increased rates of all-cause (HR 1.16; 95%CI 1.03–1.30) and CVD mortality (HR 1.49; 95%CI 1.20–1.85) compared to participants with no weight loss. We found no association between weight loss and cancer mortality. We conclude that previous and repeated weight loss may increase all-cause and CVD mortality, especially in men.

INTRODUCTION Body weight dissatisfaction, when current and desired Body Mass Index (BMI) do not align, is common in persons with obesity. The aim of this cross-sectional study was to explore factors associated with the differences between current and desired BMI, and ideal BMI (defined in the present study as BMI 25 kg/m2), in persons with obesity. METHODS Swedish citizens aged 20–64 years, residing in the Stockholm County were randomly selected from the population register at five different and evenly separated occasions in the study period 1998-2000, and invited to provide self-reported data about their current weight, height, desired weight, and other characteristics such as depressive symptoms and alcohol intake. Among the 10 441 participants with a mean of BMI 24 kg/m2, differences between desired BMI and ideal BMI were calculated to determine the discrepancy between desired BMI and ideal BMI in participants with obesity (n=808). The discrepancy between current and desired BMI was also determined. Using linear regression, factors associated with BMI discrepancies were determined. RESULTS Persons with BMI 0.05). CONCLUSION Desired BMI and discrepancies between current, desired, and ideal BMI vary according to current BMI, sex, and presence of major depression. This underscores the significance of a patient-centered approach in the management of obesity, where the goals and needs of each patient should be considered.

Abstract Background A healthy diet and a sufficient amount of physical activity are important factors to reduce complications of type 2 diabetes. Diet and physical activity are associated behaviours. Individuals who are physically active have also been shown to have healthier eating habits than sedentary individuals. We aimed to evaluate the indirect effect of a smartphone-based physical activity intervention on dietary habits in patients with type 2 diabetes. Methods We performed analyses of secondary outcomes in a randomized controlled trial. The active intervention was use of a smartphone application to promote physical activity during 12 weeks. Dietary intake was assessed at baseline and after three months using a validated semi-quantitative food frequency questionnaire comprising 94 items. We analysed changes in the intake of fruit and vegetables, snacks, fibre, whole grains, vitamin C, saturated fat, unsaturated fat and total energy. We also assessed overall dietary habits using a dietary index developed by the Swedish National Board of Health and Welfare. Results were compared between the intervention and control group, as well as stratified by sex within the study groups. Paired t-tests and analysis of covariance were performed. Results A total of 181 patients were recruited to the DiaCert-study, whereof 146 patients had complete dietary data and were included in the analyses. Women in the intervention group had a higher fruit and vegetable intake (p = 0.008) and a higher dietary index (p = 0.007), at three-months compared to women in the control group. They had increased their daily intake of fruit and vegetables by on average 87.4 g/day (p = 0.04) and improved their dietary index by on average 0.8 points (p = 0.01) from baseline to follow-up. No effect was found in men. Conclusions Women, but not men, receiving a smartphone-based physical activity intervention improved their total intake of fruit and vegetables. The transfer effect, i.e. an intervention aimed at promoting one health behavior that facilitates changes in other health behaviors, may differ between the sexes. Trial registration ClinicalTrials.gov Identifier: NCT03053336; 15/02/2017.

Abstract Background Type 2 diabetes mellitus is associated with an increased risk of impaired quality of life. Improving health related quality of life (HRQoL) is therefore an important goal in the multimodal management of diabetes. The aim of this study was to evaluate whether the use of the smartphone app DiaCert, that encourage physical activity by promoting daily steps, also impacts HRQoL in patients with type 2 diabetes. Methods In this randomized controlled trial, a total of 181 participants with type 2 diabetes were recruited from six health care centers in Stockholm, Sweden. At baseline, participants were randomized 1:1 to the use of the smartphone app DiaCert for a 3 month physical activity intervention in addition to routine care, or to a control group with routine care only. HRQoL was measured using the RAND-36 questionnaire at baseline and at follow-up after 3 months and 6 months. We analysed the HRQoL scores within the intervention and the control groups, respectively, using the Wilcoxon signed-rank test. Between group differences including intervention effect after the 3 month long intervention and after 6 months of follow-up, were assessed using generalized estimating equation models. Results In total, 166 participants, 108 men and 58 women, with complete baseline data on RAND-36 were included in analysis. The mean age was 60.2 (SD 11.4) years and the mean Body Mass Index 30.3 (SD 5.4) kg/m2. The intervention effect, expressed in terms of the difference in change in HRQoL from baseline to follow-up after 3 months of intervention, showed improvement in the health concept role limitations due to physical health problems (− 16.9; 95% CI − 28.5 to − 5.4), role limitations due to emotional problems (− 13.9; 95% CI − 25.8 to − 2.1), and emotional well-being (− 5.7; 95% CI − 10.4 to − 1.0), in the intervention group compared to the control group. No intervention effect was seen at follow-up after 6 months. Conclusions Being randomized to use the smartphone app DiaCert promoting physical activity for 3 months, improved aspects of both physical and emotional HRQoL in patients with type 2 diabetes compared to routine care, but the effect did not last 3 months after the intervention ended. Trial Registration ClinicalTrials.gov Identifier: NCT03053336.

Abstract Background The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. Methods Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and β-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. Results Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low β-cell function (LRLB), low-risk high β-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk β-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. Conclusions Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.

Abstract Background Adolescents and young adults around the world experience high rates of weight gain. The underlying eating behaviours that may lead to overconsumption of energy are complex and can depend on a number of factors. The aim of this study was to explore if eating behaviour among adolescents and young adults referred to specialized obesity treatment differed depending on sex, body composition, and parental country of birth. Methods Adolescents and young adults aged 16–25 years, referred for obesity treatment in 2018–2021 were included in the study. Eating behaviour was assessed using the Three Factor Eating Questionnaire, comprising domains of uncontrolled-, emotional- and cognitive restraint eating. Student’s t-test was used to compare differences in eating behaviour scores between males and females, and between those having at least one parent born in a Nordic country and those with both parents born outside the Nordic countries. Associations between BMI, waist circumference, and body fat percentage, and eating behaviour as the dependent variable, were examined using linear regression. Results A total of 463 participants, mean age 21 years and mean BMI 41.3 kg/m2, were included in the analysis. Females scored statistically significantly higher than males on emotional eating (45.8 vs. 35.4, p = 0.002) and cognitive restraint eating (45.4 vs. 39.2, p = 0.009). Participants with at least one parent born in a Nordic country reported a statistically significantly lower score of uncontrolled eating (45.7 vs. 51.3, p = 0.02) compared to participants with both parents born outside the Nordic countries. Further, there were statistically significant inverse associations between cognitive restraint eating scores and BMI (β=-0.64, 95%CI: -0.97 to -0.31), waist circumference (β=-0.44, 95%CI: -0.61 to -0.27) and body fat percentage (β=-0.57, 95%CI: -1.01 to -0.14) in models adjusted for age, sex, smoking, and civil status. Conclusion Our findings suggest that sex and parental country of birth may influence eating behaviours among adolescents and young adults referred for specialist obesity treatment. We also found that cognitive restraint eating decreased with increasing BMI, waist circumference, and body fat percentage. This indicates that there may be an inverse association between the ability to restrain oneself from eating and gaining weight, however, the direction of the association must be investigated further. Increased knowledge about eating behaviours may be valuable in the clinical setting.

International Registered Report Identifier (IRRID)RR2-10.1186/s12889-018-5026-4

Introduction Previous weight loss attempts in young people with obesity may have influenced their beliefs about themselves and contributed to maladaptive eating behaviors. Therefore, we aimed to investigate the association between previous weight loss with self-esteem and different eating behaviors in adolescents and young adults with obesity seeking specialty obesity care. Methods We performed a cross-sectional study, where a total of 224 participants with obesity, aged 16-25, self-reported the amount and the frequency of previous weight loss of 5 kg or more. Self-esteem was assessed with Rosenberg’s Self-Esteem Scale and eating behavior with the Three-Factor Eating Questionnaire-Revised21. Linear regression was used to analyze associations between the amount of weight loss (no weight loss, 5-10 kg, and >10 kg) and the frequency of weight loss >5 kg (0, 1, and >2 times) with self-esteem and eating behaviors. Results We found that both those who had lost 5-10 kg and those who had lost >5 kg twice or more, had statistically significantly higher cognitive restraint eating scores β=7.03 (95%CI: 0.004 to 14.05) and β=8.32 (95%CI: 1.20 to 15.43), respectively, compared to those who reported no previous weight loss. No other statistically significant associations were found. Discussion/Conclusion Previous weight loss in adolescents and young adults with obesity may be associated with a higher cognitive restraint eating behavior. Therefore, assessing weight loss history and eating behavior may be beneficial to better individualize obesity treatment.

Abstract Background Physical inactivity is a known risk factor for cardiovascular disease, but it is unclear if total and leisure time activity have different impact on the risk of myocardial infarction and stroke. In this cohort, we aimed to investigate the associations between both total and leisure time physical activity in detail, and the risks of myocardial infarction and stroke, both overall and for men and women separately. Methods We assessed the association between total and leisure time physical activity on the risk of myocardial infarction and stroke in a cohort of 31,580 men and women through record linkages from 1997–2016. We used Cox proportional hazards regression models to estimate hazard ratios (HR) with 95% confidence intervals (CI) based on detailed self-reported physical activity. In the adjusted analyses, we included age, sex, body mass index, level of education, cigarette smoking, alcohol consumption, diabetes, lipid disturbance and hypertension as potential confounders. Results We identified 1,621 incident cases of myocardial infarction and 1,879 of stroke. Among men, there was an inverse association between leisure time activity and myocardial infarction in the third tertile compared to the first (HR: 0.78; 95% CI: 0.62–0.98; p for trend = 0.03). We also found an inverse association between leisure time activity and stroke in the third tertile compared to the first (HR: 0.78; 95% CI: 0.61–0.99; p for trend = 0.04), while the corresponding HR for stroke among women was 0.91; 95% CI: 0.74–1.13. We found no significant association between total physical activity and MI (HR: 1.12; 95% CI: 0.93–1.34) or stroke (HR: 1.14 95% CI: 0.94–1.39) comparing the highest to the lowest tertile in men. Women in the highest tertile of total physical activity had a 22% lower risk of myocardial infarction compared to the lowest tertile (HR: 0.78; 95% CI: 0.63–0.97; p for trend = 0.02) and an 8% (95% CI: 0.87–0.98) reduced risk of myocardial infarction with each 1 METh/day increase of leisure time physical activity. Conclusion Total physical activity was inversely associated with the risk of myocardial infarction in women, while leisure time physical activity was inversely associated with the risk of myocardial infarction and stroke in men.

BackgroundThere is a need to find new methods that can enhance the individuals’ engagement in self-care and increase compliance to a healthy lifestyle for the prevention of noncommunicable diseases and improved quality of life. Mobile health (mHealth) apps could provide large-scale, cost-efficient digital solutions to implement lifestyle change, which as a corollary may enhance quality of life. ObjectiveHere we evaluate if the use of a smartphone-based self-management system, the Health Integrator app, with or without telephone counseling by a health coach, had an effect on clinical variables (secondary outcomes) of importance for noncommunicable diseases. MethodsThe study was a 3-armed parallel randomized controlled trial. Participants were randomized to a control group or to 1 of 2 intervention groups using the Health Integrator app with or without additional telephone counseling for 3 months. Clinical variables were assessed before the start of the intervention (baseline) and after 3 months. Due to the nature of the intervention, targeting lifestyle changes, participants were not blinded to their allocation. Robust linear regression with complete case analysis was performed to study the intervention effect among the intervention groups, both in the entire sample and stratifying by type of work (office worker vs bus driver) and sex. ResultsComplete data at baseline and follow-up were obtained from 205 and 191 participants, respectively. The mean age of participants was 48.3 (SD 10) years; 61.5% (126/205) were men and 52.2% (107/205) were bus drivers. Improvements were observed at follow-up among participants in the intervention arms. There was a small statistically significant effect on waist circumference (β=–0.97, 95% CI –1.84 to –0.10) in the group receiving the app and additional coach support compared to the control group, but no other statistically significant differences were seen. However, participants receiving only the app had statistically significantly lower BMI (β=–0.35, 95% CI –0.61 to –0.09), body weight (β=–1.08, 95% CI –1.92 to –0.26), waist circumference (β=–1.35, 95% CI –2.24 to –0.45), and body fat percentage (β=–0.83, 95% CI –1.65 to –0.02) at follow-up compared to the controls. There was a statistically significant difference in systolic blood pressure between the two intervention groups at follow-up (β=–3.74, 95% CI –7.32 to –0.16); no other statistically significant differences in outcome variables were seen. ConclusionsParticipants randomized to use the Health Integrator smartphone app showed small but statistically significant differences in body weight, BMI, waist circumference, and body fat percentage compared to controls after a 3-month intervention. The effect of additional coaching together with use of the app is unclear. Trial RegistrationClinicalTrials.gov NCT03579342; https://clinicaltrials.gov/ct2/show/NCT03579342 International Registered Report Identifier (IRRID)RR2-10.1186/s12889-019-6595-6

BackgroundeHealth interventions have the potential to increase the efficiency and effectiveness of health care. However, research has shown that implementing eHealth in routine health care practice is difficult. Organizational readiness to change has been shown to be central to successful implementation. This paper describes the development and formative evaluation of a generic self-help tool, E-Ready, designed to be used by managers, project leaders, or others responsible for implementation in a broad range of health care settings. ObjectiveThe aim of this study is to develop and evaluate a tool that could facilitate eHealth implementation in, for example, health care. MethodsA first version of the tool was generated based on implementation theory (E-Ready 1.0). A formative evaluation was undertaken through expert panels (n=15), cognitive interviews (n=17), and assessment of measurement properties on E-Ready items from 3 different workplaces (n=165) using Rasch analyses. E-Ready 1.0 was also field tested among the target population (n=29). Iterative revisions were conducted during the formative evaluation process, and E-Ready 2.0 was generated. ResultsThe E-Ready Tool consists of a readiness assessment survey and a hands-on manual. The survey measures perceived readiness for change (willingness and capability) at individual and collective levels: perceived conditions for change at the workplace, perceived individual conditions for change, perceived support and engagement among management, perceived readiness among colleagues, perceived consequences on status quo, and perceived workplace attitudes. The manual contains a brief introduction, instructions on how to use the tool, information on the themes of E-Ready, instructions on how to create an implementation plan, brief advice for success, and tips for further reading on implementation theory. Rasch analyses showed overall acceptable measurement properties in terms of fit validity. The subscale Individual conditions for change (3 items) had the lowest person reliability (0.56), whereas Perceived consequences on status quo (5 items) had the highest person reliability (0.87). ConclusionsE-Ready 2.0 is a new self-help tool to guide implementation targeting health care provider readiness and engagement readiness ahead of eHealth initiatives in, for example, health care settings. E-Ready can be improved further to capture additional aspects of implementation; improvements can also be made by evaluating the tool in a larger sample.

Objective Several, but not all studies, have shown a dose-dependent inverse association with alcohol consumption and rheumatoid arthritis (RA), whereas smoking is an established risk factor for RA. We aimed to study the association between alcohol consumption and RA incidence and investigate a potential interaction between alcohol and smoking habits, regarding RA incidence.Methods We used a prospective cohort study, based on 41 068 participants with detailed assessment of alcohol intake, smoking and potential confounders at baseline in 1997. We ascertained a total of 577 incident cases of RA during a mean of 17.7 years of follow-up through linkage to nationwide and essentially complete databases. Multivariate Cox proportional hazards models were used to estimate HR with 95% CI. Interaction on the additive scale between alcohol and smoking was estimated by calculating the attributable proportion due to interaction (AP).Results Overall, alcohol consumption was associated with a 30% reduced incidence of RA (HR 0.69, 95% CI 0.55 to 0.86) with a dose–response relationship (p value for trend

Abstract Background Mobile health, mHealth is recognized as a strategy to improve lifestyle behaviors. Research targeting specific lifestyle behaviors has shown that interventions using smartphones can be effective. However, few studies have evaluated solutions with multicomponent interventions, tailoring the intervention to the specific needs of the participant using a combination of mHealth and conventional treatment. To accomplish this, we developed Health Integrator, an mHealth platform with services and offers in the areas of diet, physical activity, sleeping habits, stress, alcohol and tobacco use. In the system, the user selects an area of intervention together with a health coach and set weekly goals. This study protocol presents the design and methodology of the Health Integrator Study, a randomized controlled trial to promote improved lifestyle behaviors. Methods A three-arm parallel randomized controlled trial (1:1:1) is conducted in the Stockholm County, Sweden. In total, 209 employees at a four different companies representing both white and blue collar workers, have been recruited. Participants are randomized to either a control group or to one of two intervention groups receiving a 3-month lifestyle behavior change program including either 1) use of Health Integrator and monthly health coaching sessions or 2) only Health Integrator. At baseline and follow-up after 3- and 6-months, all participants answer questionnaires assessing lifestyle behaviors and quality of life. At baseline and the 3-month follow-up (end of intervention period), weight, height, waist circumference and blood pressure are measured, and all participants wear an Actigraph accelerometer for 7 days to assess physical activity. Blood lipid profile and HbA1c are measured among all participants at baseline. If baseline measures fall outside the normal range, a second measurement is done after 3 months. Discussion The Health Integrator Intervention Study will evaluate if a personalized intervention combining mHealth and conventional programs for lifestyle change, with or without additional health coach sessions, can improve lifestyle behaviors and quality of life. Based on the results from this trial, Health Integrator can easily be implemented within a broad public. Trial registration ClinicalTrials.gov Identifier: NCT03579342. Retrospectively registered, first submitted May 8, 2018.

We herein outline the rationale for a Swedish cohort consortium, aiming to facilitate greater use of Swedish cohorts for world-class research. Coordination of all Swedish prospective population-based cohorts in a common infrastructure would enable more precise research findings and facilitate research on rare exposures and outcomes, leading to better utilization of study participants’ data, better return of funders’ investments, and higher benefit to patients and populations. We motivate the proposed infrastructure partly by lessons learned from a pilot study encompassing data from 21 cohorts. We envisage a standing Swedish cohort consortium that would drive development of epidemiological research methods and strengthen the Swedish as well as international epidemiological competence, community, and competitiveness.

Albumin is an important biochemical marker in palliative cancer care, used for assessment of nutritional status, disease severity and prognosis. Our primary aim was to investigate sex differences in the association between appetite and albumin levels in palliative cancer patients. We also aimed to study associations between appetite and C-reactive protein (CRP), Quality of Life (QoL), pain and fatigue. In the Palliative D-cohort, consisting of 266 men and 264 women, we found a correlation between appetite and albumin; low appetite, measured with the Edmonton Symptom Assessment System, correlated significantly with low albumin in men: (r = −0.33, p < 0.001), but not in women (r = −0.03, p = 0.65). In a regression analysis adjusted for confounding factors, results were similar. Lower appetite was correlated with higher CRP in men (r = 0.27, p < 0.001), but not in women (r = 0.12, p = 0.05). Appetite was correlated with QoL, fatigue and pain in both men and women; those with a low appetite had a low QoL and high fatigue- and pain-scores (p < 0.001). In conclusion, our results indicated possible sex differences in the associations between appetite and albumin, and between appetite and CRP, in palliative care patients. Understanding these associations could provide additional value for clinical practice.

BackgroundPrevious research studies have demonstrated a relationship between low levels of physical activity and high amounts of screen time in children and adolescents. However, this is usually based on self-reported data. Therefore, the aim of this cross-sectional study was to investigate the association between objectively measured smartphone screen time and physical activity among children and adolescents aged 10-15 years.MethodsDuring seven consecutive days, we objectively assessed smartphone screen time, using the SCRIIN smartphone application, and physical activity, using the SCRIIN activity tracker, in children and adolescents recruited from two schools in Stockholm County, Sweden. Moreover, the children/adolescents and their parents responded to a questionnaire, obtaining among other things: self-reported screen time, physical activity, sleep and health-related quality of life.ResultsA total of 121 children and adolescents (mean age: 12.1 ± 1.5) were included in the study. Objectively measured smartphone screen time was 161.2 ± 81.1 min/day. Mean physical activity, measured with the SCRIIN activity tracker, was 32.6 ± 16.5 active min/day. Minutes of screen time and physical activity did not differ between the children and adolescents from the two schools, despite located in different socioeconomic areas. Further, we found no association between smartphone screen time and physical activity. However, girls aged 14-15 years, had more smartphone screen time (pConclusionSmartphone screen time was not associated with physical activity level among children and adolescents aged 10-15 years.

The Publisher regrets that this article is an accidental duplication of an article that has already been published in https://doi.org/10.1016/j.sleep.2020.11.018. The duplicate article has therefore been withdrawn.The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Weight maintenance is a priority in cancer care, but weight loss is common and a serious concern. This study explores if there are sex differences in the perception of weight loss and its association to health-related quality of life (HRQoL) and body image. Cancer patients admitted to Advanced Medical Home Care were recruited to answer a questionnaire, including characteristics, the HRQoL-questionnaire RAND-36, and a short form of the Body Image Scale. Linear regression analyses stratified by sex and adjusted for age were performed to examine associations between percent weight loss and separate domains of HRQoL and body image score in men and women separately. In total, 99 participants were enrolled, of which 80 had lost weight since diagnosis. In men, an inverse association between weight loss and the HRQoL-domain physical functioning, β = −1.34 (95%CI: −2.44, −0.24), and a positive association with body image distress, β = 0.22 (95%CI: 0.07, 0.37), were found. In women, weight loss was associated with improvement in the HRQoL-domain role limitations due to physical health, β = 2.02 (95%CI: 0.63, 3.41). Following a cancer diagnosis, men appear to experience weight loss more negatively than women do. Recognizing different perceptions of weight loss may be of importance in clinical practice.

Abstract Background The global pandemic of physical inactivity represents a considerable public health challenge. Active transportation (i.e., walking or cycling for transport) can contribute to greater total physical activity levels. Mobile phone-based programs can promote behaviour change, but no study has evaluated whether such a program can promote active transportation in adults. This study protocol presents the design and methodology of The Smart City Active Mobile Phone Intervention (SCAMPI), a randomised controlled trial to promote active transportation via a smartphone application (app) with the aim to increase physical activity. Methods/design A two-arm parallel randomised controlled trial will be conducted in Stockholm County, Sweden. Two hundred fifty adults aged 20–65 years will be randomised to either monitoring of active transport via the TRavelVU app (control), or to a 3-month evidence-based behaviour change program to promote active transport and monitoring of active travel via the TRavelVU Plus app (intervention). The primary outcome is moderate-to-vigorous intensity physical activity (MVPA in minutes/day) (ActiGraph wGT3x-BT) measured post intervention. Secondary outcomes include: time spent in active transportation measured via the TRavelVU app, perceptions about active transportation (the Transport and Physical Activity Questionnaire (TPAQ)) and health related quality of life (RAND-36). Assessments are conducted at baseline, after the completed intervention (after 3 months) and 6 months post randomisation. Discussion SCAMPI will determine the effectiveness of a smartphone app to promote active transportation and physical activity in an adult population. If effective, the app has potential to be a low-cost intervention that can be delivered at scale. Trial registration ClinicalTrials.gov NCT03086837; 22 March, 2017.

Abstract Background Physical activity can decrease the risk of complications related to diabetes type 2. Feasible and scalable strategies to implement support for a healthy lifestyle for patients in primary care are needed. The aim of the DiaCert-study is to evaluate a digital healthcare platform and the effect of a 12-week long smartphone-app physical activity intervention aiming at increasing physical activity (primary outcome) and improve levels of HbA1c (glycated hemoglobin), blood lipids, blood pressure, body composition, as well as other lifestyle factors and overall health in patients with diabetes type 2. Methods/Design The DiaCert-study is a two-arm, randomized controlled trial that will include 250 patients with diabetes type 2. At baseline, participants are randomized 1:1 to intervention, i.e. use of the smartphone-app, during 12 weeks, or to a control group receiving only standard care. Physical activity and sedentary behavior, is objectively measured using the Actigraph GT3X. Biomarkers including HbA1c and blood lipids are measured in fasting blood samples. Anthropometrics include height, weight, waist circumference and body composition, and a number of lifestyle factors including sleep, diet, self-efficacy, and quality of life, are assessed through an extensive questionnaire. Measurements are made at baseline and at follow-up after 3, 6 and 12 months. Discussion Using new technology, is one way to bridge the gap between what patients need and what health care can offer. This study evaluates a new digital health care platform and will show if use of a smartphone-app to promote daily steps is an effective and feasible method to increase physical activity and improve clinical markers in patients with diabetes type 2. Trial registration ClinicalTrials.gov Identifier: NCT03053336 ; 7 Feb, 2017.

Previous studies found higher levels of physical activity to be protective against infections and that short and long sleep negatively affects the immune response. However, these relationships remain debatable. We aimed to investigate if physical activity and sleep habits affect incidence of upper respiratory tract infections (URTI) in a prospective cohort study.A total of 2,038 adults aged 25-64 years served as a random sample of the gainfully employed population of an industrial town in Sweden. Physical activity and sleep habits were estimated through self-reported questionnaires. Physical activity was expressed as metabolic energy turnover hours per day. Sleep was assessed as number of hours slept per night and its perceived quality. URTI outcome was prospectively self-reported during a 9-month follow-up period. Associations of physical activity and sleep with URTI were estimated using hurdle regression models adjusted for potential confounders.During 1,583 person-years 1,597 URTI occurred, resulting in an incidence of 1.01 infections/person-year (95% CI 0.96-1.06). The fitted regression models did not provide support for an association with physical activity or sleep habits. Factors positively associated with experiencing URTI were having children ≤ 6 years, female gender, higher education and treatment for allergy, asthma or lung cancer. Having children ≤ 6 years and female gender were related to a higher number of URTI among those experiencing URTI.We did not find any association between physical activity, sleep duration or sleep quality and the occurrence of upper respiratory tract infections in adult Swedish population.

Accurate assessment of children’s physical activity is critical in determining associations between childhood physical activity and health later in life. We have developed a web-based questionnaire, KidActive-Q, to assess physical activity in early childhood. The feasibility and reproducibility of KidActive-Q were assessed in a sample of 20 children aged 2 to 6 years. The questionnaire was distributed to parents via e-mail on two occasions. The median time required to complete KidActive-Q was 2.5 minutes. All the parents reported that the questionnaire was easy or very easy to fill. The intraclass correlations for test-retest reliability were 0.60 (95% confidence interval: 0.31-0.88) for daily time spent outdoors, and 0.85 (95% confidence interval: 0.72-0.97) for daily time watching television. Our results suggest that KidActive-Q is a user-friendly tool for assessing physical activity in early childhood. To our knowledge, this is the first web-based questionnaire specifically developed for young children.